Publication detail

Risk and Reliability Analysis of Open Reservoir Water Shortages Using Optimization

MARTON, D. KAPELAN, Z.

Original Title

Risk and Reliability Analysis of Open Reservoir Water Shortages Using Optimization

Type

conference paper

Language

English

Original Abstract

The goal of this paper was to describe how to find optimal relations between water shortage and hydropower energy based on Risk and Reliability methods. Reservoir simulation model including water losses as well as risk (reliability) model of water demand has been built up. Using NSGA II optimization method the optimization of reservoir operation has been done. For problem solving was used Multi-Objective Optimization. This approach has been applied to a real-life water reservoir called Vir 1 in the Czech Republic. Results were presented in the form of Pareto curves and data sets of reservoir outflows.

Keywords

Risk; reliability; water resources; open reservoir; reservoir operation; genetic algorithm; Non-Dominated Shorting Genetic Algorithm; NSGA II; water demand; water shortage

Authors

MARTON, D.; KAPELAN, Z.

RIV year

2014

Released

17. 12. 2014

Publisher

Elsevier

Location

Amsterdam

ISBN

1877-7058

Periodical

Procedia Engineering

Year of study

89

Number

1

State

Kingdom of the Netherlands

Pages from

1478

Pages to

1485

Pages count

8

URL

http://www.sciencedirect.com/science/article/pii/S187770581402548X

Full text in the Digital Library

http://hdl.handle.net/11012/194745

BibTex

@inproceedings{BUT111389,
  author="Daniel {Marton} and Zoran {Kapelan}",
  title="Risk and Reliability Analysis of Open Reservoir Water Shortages Using Optimization",
  booktitle="16th Water Distribution System Analysis Conference, WDSA2014 Urban Water Hydroinformatics and Strategic Planning",
  year="2014",
  series="Procedia Engineering",
  journal="Procedia Engineering",
  volume="89",
  number="1",
  pages="1478--1485",
  publisher="Elsevier",
  address="Amsterdam",
  doi="10.1016/j.proeng.2014.11.433",
  issn="1877-7058",
  url="http://www.sciencedirect.com/science/article/pii/S187770581402548X"
}